Information fusion strategies from distributed filters in packet-drop networks

Abstract-- In this paper we study different distributed estimation schemes for stochastic discrete time linear systems where the communication between the sensors and the estimation center is subject to random packet loss. Sensors are provided with computational and memory resources so that they can potentially perform data processing of the measurements before sending their information. In particular, we explore three different strategies. The first, named measurement fusion (MF), optimally fuses the raw measurements received so far from all sensors. The second strategy, named optimal partial estimate fusion (OPEF), optimally fuses at the central node the last local state estimates received from each sensor. The last strategy, named open loop partial estimate fusion (OLPEF), simply sums local state estimates received from each sensor and replace the lost ones with their open loop counterpart. We provide some analytical results about the performance of these three schemes in special re...

• Type: Conference
• Year: 2008
• Where: CDC
• Authors: Alessandro Chiuso, Luca Schenato
• Keywords: CDC 2008, Control Systems, Local State Estimates, Partial Estimate Fusion, Sensors